Final answer:
Experimental probability involves determining the likelihood of an event based on actual outcomes from an experiment, such as the number of heads in a series of coin flips, divided by the total trials, and contrasts with theoretical probability which is predicted based on possible outcomes.
Step-by-step explanation:
An example of experimental probability is calculating the number of times a certain outcome occurs in an experiment and dividing it by the total number of trials. An experiment involves events such as flipping a coin, rolling a pair of dice, or drawing a marble from a bag. If a particular event, such as obtaining heads, occurs so many times out of a certain number of coin flips, then this frequency can be used to determine the experimental probability of getting heads.
For instance, if a fair coin is tossed 100 times and heads come up 53 times, then the experimental probability of tossing a head would be 53/100 = 0.53. This contrasts with theoretical probability, which does not rely on actual outcomes but rather on the expected likelihood of an event occurring, based on the possible outcomes of the experiment.
When considering probabilities in terms of long-term relative frequency, this is described by the law of large numbers, which predicts that as an experiment is repeated many times, the relative frequency of an outcome will approach its theoretical probability.